Evidence map›Paper›PMID 26608022›Full record

ArticleBMC pregnancy and childbirth2015

Medication use during pregnancy, gestational age and date of delivery: agreement between maternal self-reports and health database information in a cohort.

Federica Edith Pisa, Anica Casetta, Elena Clagnan, Elisa Michelesio, Liza Vecchi Brumatti, Fabio Barbone

Abstract read
In one paragraph

Article in BMC pregnancy and childbirth, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
37citing papers in PubMed, 3 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

37 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Observational
  15. Article
  16. Interaction between Maternal Immune Activation and Antibiotic Use during Pregnancy and Child Risk of Autism Spectrum Disorder.Autism research : official journal of the International Society for Autism Research · 2020
    Article
  17. Article
  18. Article
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Federica Edith PisaInstitute of Hygiene and Clinical Epidemiology, University Hospital of Udine, Via Colugna 50, 33100, Udine, Italy. federica.pisa@uniud.it.
Anica CasettaDepartment of Medical and Biological Sciences, University of Udine, Udine, Italy. anica.casetta@uniud.it.
Elena ClagnanDirezione Centrale Salute, Integrazione Socio Sanitaria e Politiche Sociali, Regione Friuli Venezia Giulia, Udine, Italy. elena.clagnan@regione.fvg.it.
Elisa MichelesioINSIEL SpA, Udine, Italy. elisa.michelesio@insiel.it.
Liza Vecchi BrumattiScientific Direction, Institute for Maternal and Child Health - IRCCS "Burlo Garofolo", Trieste, Italy. vecchi@burlo.trieste.it.
Fabio BarboneInstitute of Hygiene and Clinical Epidemiology, University Hospital of Udine, Via Colugna 50, 33100, Udine, Italy. fabio.barbone@uniud.it.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHealth databases are a promising resource for epidemiological studies on medications safety during pregnancy. The reliability of information on medications exposure and pregnancy timing is a key methodological issue. This study (a) compared maternal self-reports and database information on medication use, gestational age, date of delivery; (b) quantified the degree of agreement between sources; (c) assessed predictors of agreement.

methodsPregnant women recruited in a prenatal clinic in Friuli Venezia Giulia (FVG) region, Italy, from 2007 to 2009, completed a questionnaire inquiring on medication use during pregnancy, gestational age and date of delivery. Redeemed prescriptions and birth certificate records were extracted from regional databases through record linkage. Percent agreement, Kappa coefficient, prevalence and bias-adjusted Kappa (PABAK) were calculated. Odds Ratio (OR), with 95% confidence interval (95% CI), of ≥ 1 agreement was calculated through unconditional logistic regression.

resultsThe cohort included 767 women, 39.8% reported medication use, and 70.5% were dispensed at least one medication. Kappa and PABAK indicated almost perfect to substantial agreement for antihypertensive medications (Kappa 0.86, PABAK 0.99), thyroid hormones (0.88, 0.98), antiepileptic medications (1.00, 1.00), antithrombotic agents (0.70, 0.96). PABAK value was greater than Kappa for medications such as insulin (Kappa 0.50, PABAK 0.99), antihistamines for systemic use (0.50, 0.99), progestogens (0.28, 0.79), and antibiotics (0.12, 0.63). Adjusted OR was 0.48 (95% CI 0.26; 0.90) in ex- vs. never smokers, 0.64 (0.38; 1.08) in < high school vs. university, 1.55 (1.01; 2.37) in women with comorbidities, 2.25 (1.19; 4.26) in those aged 40+ vs. 30-34 years. Gestational age matched exactly in 85.2% and date of delivery in 99.5%.

conclusionsFor selected medications used for chronic conditions, the agreement between self-reports and dispensing data was high. For medications with low to very low prevalence of use, PABAK provides a more reliable measure of agreement. Maternal reports and dispensing data are complementary to each other to increase the reliability of information on the use of medications during pregnancy. Birth certificates provide reliable data on the timing of pregnancy. FVG health databases are a valuable source of data for pregnancy research.

Indexed as

Medical RecordsSelf ReportAdultBirth CertificatesComorbidityDatabases, FactualDelivery, ObstetricDrug PrescriptionsFemaleGestational AgeHumansItalyLogistic ModelsOdds RatioPregnancyPrenatal Care

Identifiers

PMID26608022
PMCPMC4660837

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.